Mitigating risk with real-time credit information

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In the current uncertain climate, it can be difficult for some businesses to fully predict the state of the future credit landscape. However, what is clear is that it will be defined by two key aspects: the quality of data and the way it is delivered and utilised by organisations. Much more emphasis is now being placed on data needing to be live and current to provide true insight.

While a simple online search can reveal the credit history of a potential client, it’s much harder to assess the viability of a potential transaction using this level of data. Mitigating risk now hinges more greatly on the use of live dynamic data such as fraud analysis, trade payment data, CCJ or legal information. Granular data of this nature can help facilitate judgements that finance professionals need to make.

When looking at the delivery aspect, a much greater number of companies over the last few years are now demanding real-time data that is delivered directly to their accounting or CRM platforms, plus live ledger platforms that allows finance professionals to compare their own data with that of a credit reference agency. A combination of existing data and this market information can help address areas where organisations are most at risk from bad debt.

Planning for 2021

The onset of the Covid-19 pandemic in March 2020 understandably left CFOs struggling to make financial plans for their businesses due to uncertainty, with no relevant historical data to draw predictions from. However now, with almost 12 months of historical internal data having been accumulated and the promise of life returning to normality thanks to lockdowns easing, businesses are in a better position to more accurately plan for 2021. In fact, two-thirds of UK-based CFOs predict that the demand for their goods and services will have returned to pre-pandemic levels by the end of 2021, which has no doubt been spurred on by the rapid rollout of the vaccine programme.

The last twelve months have served to highlight that financial plans do need to be reviewed regularly. Whilst quarterly analyses were previously seen to be prudent, with the need for dynamic agile planning at the forefront of many business leader’s minds, demand for real-time data to fuel is greater than ever. While there’s much to be optimistic about this year, risk and reward does need to be balanced. The finance companies that survive the upcoming period will be those that know how, where and when to invest their money with the right data insights to inform their decisions.

The impact of fraud on financial risk

While any bad debt can be detrimental to businesses, the impact of fraud can lead to bigger problems for organisations that provide assets such as machinery and vehicles as these could potentially go missing in the process. Evidence is showing that financial fraud is increasing year-on-year, and there are two types which are posing the most risk to businesses. One is fraudsters posing as existing businesses in order to make transactions with suppliers, and the other is the creation of fake companies by criminals.

There are some simple things that businesses can do to spot a fake company. Data such as the names of directors and address of the business wanting to make the transaction needs to be up-to-date so it can be checked and verified to ensure it is genuine. Other giveaways can be that the credit information of the company is filed a month after year-end, or a brand-new company has made an unrealistic amount of profit in its first year. While credit managers have a responsibility to ensure that their credit control and sales teams spot for unusual details or orders that look too good to be true, human error or oversight is always a possibility. Real-time data from credit reference agencies can play a key role here in helping teams assess the financial position of the company that wishes to do business. Algorithms and other tools such as automated intelligence can also be used to analyse this data, ensuring suspicious companies are flagged before harm can be done.

Trusting data to provide risk insight

Older credit information is no doubt of greater risk to a business, so this is where dynamic data is providing much of the real-time insight and can augment the file data already being analysed. While it’s true that the delay of financial reporting by three months in the UK due to the pandemic has made it harder for business decisions to be made, organisations should look to external data from previous years to help provide insight. Next to this historic data most credit information bureaus provide near time payment market experiences often referred to as payment trade data. This additional data source proofs to be a predictive source of information to base reliable credit decisions on.

So how can a credit controller or manager build a business case for their company to invest in the tools and associated data to help them mitigate financial risks? It’s as simple as conveying the return-on-investment from purchasing these tools. The initial investment in technology may be large, but it can provide insights that can allow money to be saved in the long-term.
The smarter way is to spend more money in the correct initial investment that provides useful real-time data, and not rely on cheaper solutions, which can hinder businesses in the long-term. Retrospective analysis of where bad debt has been accumulated previously can also help inform future decisions. Ultimately, financial organisations and professionals should always expect the unexpected and adapt to change where possible in order to mitigate any future risks.

Listen back to the recent Visma | Onguard webinar to hear Steve Kilsby & Ian Wright of Credit Assist talk about the future landscape of credit information, the role of real-time data in mitigating risk and why it doesn’t always pay to buy cheap!

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